A Similarity-Based Approach for Improving the Efficiency of Drawing Spatiotemporal Point Features

ABSTRACT

The mapping of spatiotemporal point features plays an important role in geovisualization. However, such mapping suffers from low efficiency due to computational redundancy when similar symbols are used to visualize spatiotemporal point features. This paper presents a similarity-based approach to predict and avoid computational redundancy, which improves mapping efficiency. First, to identify computational redundancy, the similarity of point symbols is measured based on commonalities in symbol graphics and symbol drawing operations. Second, a similarity-enhanced method is proposed to comprehensively predict and avoid computational redundancies when mapping spatiotemporal point features. This approach was tested using two real-world spatiotemporal datasets. The results suggest that the proposed approach offers relatively large performance improvements.